title: Simulation of realistic linac motion improves the accuracy of a Monte Carlo based VMAT plan QA system.
abstract: OBJECTIVE
  To investigate the use of a software-based pre-treatment QA system for VMAT, which incorporates realistic linac motion during delivery.
  
  
  METHODS
  A beam model was produced using the GATE platform for GEANT4 Monte Carlo dose calculations. Initially validated against static measurements, the model was then integrated with a VMAT delivery emulator, which reads plan files and generates a set of dynamic delivery instructions analogous to the linac control system. Monte Carlo simulations were compared to measurements on dosimetric phantoms for prostate and head and neck VMAT plans. Comparisons were made between calculations using fixed control points, and simulations of continuous motion utilising the emulator. For routine use, the model was incorporated into an automated pre-treatment QA system.
  
  
  RESULTS
  The model showed better agreement with measurements when incorporating linac motion: mean gamma pass (Γ<1) over 5 prostate plans was 100.0% at 3%/3mm and 97.4% at 2%/2mm when compared to measurement. For the head and neck plans, delivered to the anatomical phantom, gamma passes were 99.4% at 4%/4mm and 94.94% at 3%/3mm. For example simulations within patient CT data, gamma passes were observed which are within our centre's tolerance for pre-treatment QA.
  
  
  CONCLUSIONS
  Through comparison to phantom measurements, it was found that the incorporation of a realistic linac motion improves the accuracy of the model compared to the simulation of fixed control points. The ability to accurately calculate dose as a second check of the planning system, and determine realistic delivery characteristics, may allow for the reduction of machine-based pre-treatment plan QA for VMAT.
authors.affiliation: Christie Medical Physics and Engineering (CMPE), The Christie NHS Foundation Trust, Manchester, UK; Manchester Academic Health Science Centre (MAHSC), Faculty of Medical and Human Sciences, University of Manchester, UK. Electronic address: christopher.boylan@christie.nhs.uk.
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Boylan
authors.forename: Adam H
authors.initials: AH
authors.lastname: Aitkenhead
authors.forename: Carl G
authors.initials: CG
authors.lastname: Rowbottom
authors.forename: Ranald I
authors.initials: RI
authors.lastname: Mackay
mesh_terms: D003198:Computer Simulation; D006258:Head and Neck Neoplasms / Q000532:radiotherapy*; D006801:Humans; D008297:Male; D009010:Monte Carlo Method; D010315:Particle Accelerators; D019047:Phantoms, Imaging; D011471:Prostatic Neoplasms / Q000532:radiotherapy*; D011785:Quality Assurance, Health Care; D011874:Radiometry / Q000379:methods; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software
keywords: Monte Carlo; Quality assurance; Treatment verification; VMAT